How to recommend?: User trust factors in movie recommender systems

Shlomo Berkovsky; Ronnie Taib; Dan Conway

doi:10.1145/3025171.3025209

How to recommend?

User trust factors in movie recommender systems

Shlomo Berkovsky, Ronnie Taib, Dan Conway

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution

31 Citations (Scopus)

Abstract

How much trust a user places in a recommender is crucial to the uptake of the recommendations. Although prior work established various factors that build and sustain user trust, their comparative impact has not been studied in depth. This paper presents the results of a crowdsourced study examining the impact of various recommendation interfaces and content selection strategies on user trust. It evaluates the subjective ranking of nine key factors of trust grouped into three dimensions and examines the differences observed with respect to users' personality traits.

Original language	English
Title of host publication	Proceedings of the 22nd International Conference on Intelligent User Interfaces
Place of Publication	New York
Publisher	Association for Computing Machinery (ACM)
Pages	287-300
Number of pages	14
ISBN (Electronic)	9781450343480
DOIs	https://doi.org/10.1145/3025171.3025209
Publication status	Published - 2017
Externally published	Yes
Event	22nd International Conference on Intelligent User Interfaces, IUI 2017 - Limassol, Cyprus Duration: 13 Mar 2017 → 16 Mar 2017

Other

Other	22nd International Conference on Intelligent User Interfaces, IUI 2017
Country	Cyprus
City	Limassol
Period	13/03/17 → 16/03/17

Keywords

recommender systems
user-system trust
presentation of recommendations
user study
Presentation of recommendations
User study
User-system trust
Recommender systems

Access to Document

10.1145/3025171.3025209

Link to publication in Scopus

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Cite this

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title = "How to recommend?: User trust factors in movie recommender systems",

abstract = "How much trust a user places in a recommender is crucial to the uptake of the recommendations. Although prior work established various factors that build and sustain user trust, their comparative impact has not been studied in depth. This paper presents the results of a crowdsourced study examining the impact of various recommendation interfaces and content selection strategies on user trust. It evaluates the subjective ranking of nine key factors of trust grouped into three dimensions and examines the differences observed with respect to users' personality traits.",

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Berkovsky, S, Taib, R & Conway, D 2017, How to recommend? User trust factors in movie recommender systems. in Proceedings of the 22nd International Conference on Intelligent User Interfaces. Association for Computing Machinery (ACM), New York, pp. 287-300, 22nd International Conference on Intelligent User Interfaces, IUI 2017, Limassol, Cyprus, 13/03/17. https://doi.org/10.1145/3025171.3025209

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AU - Taib, Ronnie

AU - Conway, Dan

PY - 2017

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KW - user-system trust

KW - presentation of recommendations

KW - user study

KW - Presentation of recommendations

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